Morphologic identification of clinically encountered moulds using a residual neural network

The use of morphology to diagnose invasive mould infections in China still faces substantial challenges, which often leads to delayed diagnosis or misdiagnosis. We developed a model called XMVision Fungus AI to identify mould infections by training, testing, and evaluating a ResNet-50 model. Our res...

Descripción completa

Detalles Bibliográficos
Autores principales: Jing, Ran, Yin, Xiang-Long, Xie, Xiu-Li, Lian, He-Qing, Li, Jin, Zhang, Ge, Yang, Wen-Hang, Sun, Tian-Shu, Xu, Ying-Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Microbiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614265/
https://www.ncbi.nlm.nih.gov/pubmed/36312928
http://dx.doi.org/10.3389/fmicb.2022.1021236

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614265/
https://www.ncbi.nlm.nih.gov/pubmed/36312928
http://dx.doi.org/10.3389/fmicb.2022.1021236

Ejemplares similares